No, Maybe and Close Enough - Using Probabilistic Data Structures in Python
Explore probabilistic data structures in Python for efficient counting and item recognition, focusing on Hyperloglog and Bloom Filter algorithms for fast, scalable solutions.
Secure Software Supply Chains for Python
Explore Python software supply chain security, including common attacks, protective measures, and tools. Learn about ecosystem improvements for enhanced security in third-party package integration.
Unexpected Execution - Wild Ways Code Execution Can Occur in Python
Explore unconventional code execution methods in Python, from yaml to str.format. Learn about real vulnerabilities, absurd exploits, and prevention techniques using Facebook's open-source Pysa analyzer.
Statistical Typing - A Runtime Typing System for Data Science and Machine Learning
Statistical typing: A runtime typing system for data science and ML, extending primitive types to statistical data types. Enables multivariate schemas, generative data contracts, and easier data testing with pandera.
The Road to Pattern Matching in Python
Explore the rationale and concepts behind Python's pattern matching feature, its benefits for processing structured data, and how it complements existing tools for more efficient programming.
Gradual Typing in Practice
Explore gradual typing in Python, its benefits for code quality, and strategies for implementing types in large codebases, focusing on Instagram's experience with Pyre.
PyTesting the Limits of Machine Learning
Explore techniques and tools for testing machine learning components in Python, addressing challenges of nondeterminism and ensuring reliability in ML-driven applications.
More Fun With Hardware and CircuitPython - IoT, Wearables, and More
Explore advanced CircuitPython projects for IoT and wearables. Learn to choose devices, understand electronics basics, and add interactivity to hardware projects through exciting demos and real-world applications.
The Magic of "Self" - How Python Inserts "Self" into Methods
Explore Python's data model and descriptor protocol to understand how 'self' is automatically inserted into methods, unveiling the magic behind this core language feature.
Optimizing Data Retrieval with Python Celery
Explore asynchronous data retrieval using Python Celery to overcome browser connection limits, improve web application performance, and enhance user experience when visualizing large datasets.
Large Scale Data Validation - with Spark and Dask
Explore data validation techniques for large-scale datasets using Spark and Dask. Learn to transition from single-machine to distributed computing, combining frameworks for efficient validation across partitions.
Blackfire - Debugging Performance
Discover techniques for optimizing Django application performance using Blackfire. Learn to analyze resource consumption, meet performance budgets, and seamlessly integrate performance testing across development stages.
Python - The Next Generation
Discover strategies for teaching Python to secondary students and learn about its growing role in education. Join the Python education community and explore evidence-based teaching methods.
Getting an Edge with Network Analysis with Python
Explore network analysis with Python to uncover hidden connections in everyday interactions, from social media to transportation, and gain insights into their impact on our lives.
Your App Is Async So Take Advantage of It for Development
Explore how Python's async capabilities enable real-time app inspection, remote REPLs, and graphical visualizations for enhanced development and debugging experiences.
Dask-SQL - Empowering Pythonistas for Scalable End-to-End Data Engineering
Explore dask-sql for Python-based SQL data extraction from enterprise datalakes, enabling seamless integration with PyData tools for machine learning, analytics, and data transformation workflows.
PyKnit - Math Tools for Knitters
Explore pyKnit, an open-source toolkit for knitters to customize patterns, adjust sizing, and simplify complex math calculations, making knitting more accessible and inclusive for all skill levels.
Testing Stochastic AI Models with Hypothesis
Explore property-based testing for AI models using Hypothesis library, focusing on generating random edge cases and defining system properties and specifications.
What We Learned from Papermill to Operationalize Notebooks
Explore notebook automation with Papermill, learning parameterization techniques and execution strategies to enhance troubleshooting pipelines and empower on-call developers.
Scalene - A High-Performance, High-Precision CPU+GPU+Memory Profiler for Python
Discover Scalene: a revolutionary Python profiler offering unparalleled speed and precision for CPU, GPU, and memory analysis, with unique features like GPU profiling and memory leak detection.
Packaging Python in 2021
Explore the evolving Python packaging landscape, focusing on pyproject.toml's rise and setup.py's decline. Learn about modern alternatives and best practices for efficient project setup.